API cost decision in 10 seconds

NewLFM3-1.7B vs NewParticle-1

Pick LFM3-1.7B for lower cost; pick Particle-1 only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick LFM3-1.7B for lower cost; pick Particle-1 only if the larger context window matters more.

On the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $0.3 for Particle-1, saving $0.12 (40% lower).

Cost-first pickLFM3-1.7B
Context-first pickParticle-1
Sample savings$0.1240%
10x traffic gap$1.2

Particle-1 has more context, but LFM3-1.7B saves $0.12 on the standard workload. At 10x that traffic, the same price gap is about $1.2. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Tie, balanced workload favors LFM3-1.7B, and output-heavy chatbot favors LFM3-1.7B.

Workload shapeToken mixBetter pickLFM3-1.7BParticle-1
Input-heavy / RAG5M input + 500K outputTie$0.5$0.5
Balanced workload1M input + 1M outputLFM3-1.7B$0.28$0.55
Output-heavy chatbot1M input + 5M outputLFM3-1.7B$1.08$2.55
Cheaper input Particle-1 $0.08 vs $0.05 / 1M

Particle-1 is $0.03 cheaper per 1M input tokens (37.5% lower; 1.6x difference).

Cheaper output LFM3-1.7B $0.2 vs $0.5 / 1M

LFM3-1.7B is $0.3 cheaper per 1M output tokens (60% lower; 2.5x difference).

Larger context Particle-1 262.14K vs 1.05M

Particle-1 has 786.43K more context (4x larger).

Sample workload LFM3-1.7B $0.18 vs $0.3

LFM3-1.7B is $0.12 cheaper on the standard workload (40% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
LFM3-1.7B Calculating… Estimated API cost
Particle-1 Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Particle-1 has the lower input price; LFM3-1.7B has the lower output price; Particle-1 offers the larger context window. For the 1M input plus 500K output sample, LFM3-1.7B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.18 for LFM3-1.7B and $0.3 for Particle-1.

Best Fit

Choose LFM3-1.7B when you care most about lower output-token price.

Choose Particle-1 when you care most about lower input-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $0.3 for Particle-1, saving $0.12 (40% lower).
  • LFM3-1.7B is $0.12 cheaper on the standard workload (40% lower).
  • Particle-1 is $0.03 cheaper per 1M input tokens (37.5% lower; 1.6x difference).
  • LFM3-1.7B is $0.3 cheaper per 1M output tokens (60% lower; 2.5x difference).
  • Particle-1 has 786.43K more context (4x larger).
Head-to-Head Specs
FeatureNewLFM3-1.7B
(LiquidAI)
NewParticle-1
(Particle AI)
Input Price
prompt tokens per 1M
$0.08$0.05
Completion Price
per 1M tokens
$0.2$0.5
Sample Workload Cost
1M input + 500K output
$0.18$0.3
Context Window262.14K1.05M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionLFM3-1.7BOn the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $0.3 for Particle-1, saving $0.12 (40% lower).
High-volume input processingParticle-1Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsLFM3-1.7BLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workParticle-1A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

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Larger context alternatives

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Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

LiquidAI catalog

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Particle AI catalog

Check other Particle AI models with comparable pricing, context, or release timing.

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LFM3-1.7B

A compact 1.7B-parameter text model with a 256K-token context, post-trained for agents, tool calling, and structured outputs. It reasons before it answers. Prompts and outputs may be retained and used...

Particle-1

Particle-1 is a token-efficient agentic coding model from Particle AI, post-trained on DeepSeek V4.1 Flash. It is suited for software engineering work such as terminal workflows, codebase changes, and data...